Knowledge Discovery and Data Mining FYP Report Examples

Below are some links to some previous FYP reports related to knowledge discovery and data mining on big data. Links to associated oral presentation videos are also available.

Project Title

Project Description

Link(s)

2015 PAN1Detecting New Extraordinary Events from Twitter

A system that includes data grabbing, preprocessing, text mining and clustering; a valiant attempt to perform the difficult task of text mining; disappointing results due to some time management miscalculations

2012 RAYW1Data Mining for Business Applications

Using statistical methods to find people most likely to help with viral marketing

2012 RO4Social Investment Forecasting Using Web Mining

Nice GUI, creative use of social networking data

2011 MA3Texas Holdem Poker AI Utilizing Machine Learning Techniques

Experimenting with different machine learning paradigms to find an improved means to calculate win probabilities (Only the last 32 minutes were recorded due to an early start.)

Knowledge discovery focuses on the process of extracting meaningful patterns from big data, and data mining uses automated computational and statistical tools and techniques on big data. Together, their underlying goal is to help humans make high-level sense of large volumes of low-level data, and share that knowledge with people in related fields, especially in the areas of business and politics. It can involve methods for data preparation, cleaning, and selection, use of appropriate prior knowledge, development and application of data mining algorithms, and proper results analysis. It engages methods from such diverse areas as machine learning, pattern recognition, database science, statistics and analytics, artificial intelligence, knowledge acquisition for expert systems, data modeling and visualization, and high performance computing.